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The problem is not AI code, but not knowing about system architecture or intent

388 points · 240 comments · zazuke

  1. bengold14 · · focus · HN ↗
    I see this everyday. The problem is code is the wrong abstraction for the work we do. LLMs have solved coding, but they haven't solved systems, collaboration or system maintenance.

    Edit: Since I seem to have touched a nerve - I&#x27;ve been working on a project to solve this: <a href="https:&#x2F;&#x2F;www.archme.io" rel="nofollow">https:&#x2F;&#x2F;www.archme.io if you want to know my thoughts on the right abstraction

    1. verdverm · · focus · HN ↗
      When you say &quot;solved coding,&quot; what does this mean, what does it look like?

      I have strong disagreement because it sounds like, by analogy or proxy, we have also &quot;solved writing&quot;

      1. sampullman · · focus · HN ↗
        Writing is a means of expression and communication. Code can be those things, but that&#x27;s not its primary purpose.

        I think &quot;solved coding&quot; is taking it too far, but for many projects, the mechanical aspect of it has been removed or reduced greatly.

        LLMs will have a much harder time &quot;solving writing&quot;, because they cannot develop their own style and so are severely limited, creatively. This is less important for coding.

        1. verdverm · · focus · HN ↗
          I agree that writing is much harder, largely because there is no way to get concrete feedback for &quot;does it work&quot;

          I still think they produce shoddy or sus code too often, an artifact of the current generation&#x27;s training to try anything and everything until it &quot;completes the task&quot;. They have a hard time even with that concept, which is part of &quot;coding&quot; imo

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